{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Qiskit Aer: Pulse simulation of two qubits using a Duffing oscillator model\n",
    "\n",
    "This notebook shows how to use the Qiskit Aer pulse simulator, which simulates experiments specified as pulse `Schedule` objects at the Hamiltonian level. The simulator solves the Schrodinger equation for a specified Hamiltonian model and pulse `Schedule` in the frame of the drift Hamiltonian.\n",
    "\n",
    "In particular, in this tutorial we will: \n",
    "\n",
    "- Construct a model of a two qubit superconducting system.\n",
    "- Calibrate $\\pi$ pulses on each qubit in the simulated system.\n",
    "- Observe cross-resonance oscillations when driving qubit 1 with target qubit 0.\n",
    "\n",
    "The Introduction outlines the concepts and flow of this notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Introduction <a name='introduction'></a>\n",
    "\n",
    "The main sections proceed as follows.\n",
    "\n",
    "### Section 3: Duffing oscillator model\n",
    "\n",
    "To simulate a physical system, it is necessary to specify a model. In this notebook, we will model superconducting qubits as a collection of *Duffing oscillators*. The model is specified in terms of the following parameters:\n",
    "\n",
    "-  Each Duffing oscillator is specified by a frequency $\\nu$, anharmonicity $\\alpha$, and drive strength $r$, which result in the Hamiltonian terms:\n",
    "\n",
    "$$\\begin{equation}\n",
    "    2\\pi\\nu a^\\dagger a + \\pi \\alpha a^\\dagger a(a^\\dagger a - 1) + 2 \\pi r (a + a^\\dagger) \\times D(t),\n",
    "\\end{equation}$$\n",
    "\n",
    "where $D(t)$ is the signal on the drive channel for the qubit, and $a^\\dagger$ and $a$ are, respectively, the creation and annihilation operators for the qubit. Note that the drive strength $r$ sets the scaling of the control term, with $D(t)$ assumed to be a complex and unitless number satisfying $|D(t)| \\leq 1$. \n",
    "\n",
    "-  A coupling between a pair of oscillators $(l,k)$ is specified by the coupling strength $J$, resulting in an exchange coupling term:\n",
    "\n",
    "$$\\begin{equation}\n",
    "    2 \\pi J (a_l a_k^\\dagger + a_l^\\dagger a_k),\n",
    "\\end{equation}$$\n",
    "\n",
    "where the subscript denotes which qubit the operators act on.\n",
    "\n",
    "- Additionally, for numerical simulation, it is necessary to specify a cutoff dimension; the Duffing oscillator model is *infinite dimensional*, and computer simulation requires restriction of the operators to a finite dimensional subspace.\n",
    "\n",
    "**In the code:** We will define a model of the above form for two coupled qubits using the helper function `duffing_system_model`.\n",
    "\n",
    "### Section 4: $\\pi$-pulse calibration using Ignis\n",
    "\n",
    "Once the model is defined, we will calibrate $\\pi$-pulses on each qubit. A $\\pi$-pulse is defined as a pulse on the drive channel of a qubit that \"flips\" the qubit; i.e. that takes the ground state to the first excited state, and the first excited state to the ground state.\n",
    "\n",
    "We will experimentally find a $\\pi$-pulse for each qubit using the following procedure:\n",
    "\n",
    "- A fixed pulse shape is set - in this case it will be a Gaussian pulse.\n",
    "- A sequence of experiments is run, each consisting of a Gaussian pulse on the qubit, followed by a measurement, with each experiment in the sequence having a subsequently larger amplitude for the Gaussian pulse.\n",
    "- The measurement data is fit, and the pulse amplitude that completely flips the qubit is found (i.e. the $\\pi$-pulse amplitude).\n",
    "\n",
    "**In the code:** Using Ignis we will construct `Schedule` objects for the above experiments, then fit the data to find the $\\pi$-pulse amplitudes. \n",
    "\n",
    "### Section 5: Cross-resonance oscillations\n",
    "\n",
    "Once the $\\pi$-pulses are calibrated, we will simulate the effects of cross-resonance driving on qubit $1$ with target qubit $0$. This means that we will drive qubit $1$ at the frequency of qubit $0$, with the goal of observing that the trajectory and oscillations of qubit $0$ *depends* on the state of qubit $1$. This phenomenon provides a basis for creating two-qubit *controlled* gates. Note: This section requires the calibration of the $\\pi$-pulse in Section 4.\n",
    "\n",
    "To observe cross-resonance driving, we will use experiments very similar to the $\\pi$-pulse calibration case:\n",
    "\n",
    "- Initially, qubit $1$ is either left in the ground state, or is driven to its first excited state using the $\\pi$-pulse found in Section 4.\n",
    "- A sequence of experiments is run, each consisting of a Gaussian pulse on qubit $1$ driven at the frequency of qubit $0$, followed by a measurement of both qubits, with each experiment of the sequence having a subsequently larger amplitude for the Gaussian pulse.\n",
    "\n",
    "**In the code:** Functions for defining the experiments and visualizing the data are constructed, including a visualization of the trajectory of the target qubit on the Bloch sphere."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Imports <a name='imports'></a>\n",
    "\n",
    "This notebook makes use of the following imports."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from scipy.optimize import curve_fit, root\n",
    "\n",
    "# visualization tools\n",
    "import matplotlib.pyplot as plt\n",
    "from qiskit.visualization.bloch import Bloch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import qiskit libraries for working with `pulse` and calibration:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import qiskit.pulse as pulse\n",
    "from qiskit.pulse.library import Gaussian, GaussianSquare\n",
    "from qiskit.compiler import assemble\n",
    "\n",
    "from qiskit.ignis.characterization.calibrations import rabi_schedules, RabiFitter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Imports for qiskit pulse simulator: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The pulse simulator\n",
    "from qiskit.providers.aer import PulseSimulator\n",
    "\n",
    "# function for constructing duffing models\n",
    "from qiskit.providers.aer.pulse import duffing_system_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Duffing oscillator system model <a name='duffing'></a>\n",
    "\n",
    "An object representing a model for a collection of Duffing oscillators can be constructed using the `duffing_system_model` function. Here we construct a $2$ Duffing oscillator model with cutoff dimension $3$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# cutoff dimension\n",
    "dim_oscillators = 3\n",
    "\n",
    "# frequencies for transmon drift terms, harmonic term and anharmonic term\n",
    "# Number of oscillators in the model is determined from len(oscillator_freqs)\n",
    "oscillator_freqs = [5.0e9, 5.2e9]\n",
    "anharm_freqs = [-0.33e9, -0.33e9]\n",
    "\n",
    "# drive strengths\n",
    "drive_strengths = [0.02e9, 0.02e9]\n",
    "\n",
    "# specify coupling as a dictionary (qubits 0 and 1 are coupled with a coefficient 0.002e9)\n",
    "coupling_dict = {(0,1): 0.002e9}\n",
    "\n",
    "# sample duration for pulse instructions \n",
    "dt = 1e-9\n",
    "\n",
    "# create the model\n",
    "two_qubit_model = duffing_system_model(dim_oscillators=dim_oscillators,\n",
    "                                       oscillator_freqs=oscillator_freqs,\n",
    "                                       anharm_freqs=anharm_freqs,\n",
    "                                       drive_strengths=drive_strengths,\n",
    "                                       coupling_dict=coupling_dict,\n",
    "                                       dt=dt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The function `duffing_system_model` returns a `PulseSystemModel` object, which is a general object for storing model information required for simulation with the `PulseSimulator`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4 Calibrating $\\pi$ pulses on each qubit using Ignis <a name='rabi'></a>\n",
    "\n",
    "As described in the introduction, we now calibrate $\\pi$ pulses on each qubit in `two_qubit_model`. The experiments in this calibration procedure are known as *Rabi experiments*, and the data we will observe are known as *Rabi oscillations*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1 Constructing the schedules\n",
    "\n",
    "We construct the schedules using the `rabi_schedules` function in Ignis. To do this, we need to supply an `InstructionScheduleMap` containing a measurement schedule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# list of qubits to be used throughout the notebook\n",
    "qubits = [0, 1]\n",
    "\n",
    "# Construct a measurement schedule and add it to an InstructionScheduleMap\n",
    "meas_amp = 0.025\n",
    "meas_samples = 1200\n",
    "meas_sigma = 4\n",
    "meas_width = 1150\n",
    "meas_pulse = GaussianSquare(duration=meas_samples, amp=meas_amp,\n",
    "                            sigma=meas_sigma, width=meas_width)\n",
    "\n",
    "acq_sched = pulse.Acquire(meas_samples, pulse.AcquireChannel(0), pulse.MemorySlot(0))\n",
    "acq_sched += pulse.Acquire(meas_samples, pulse.AcquireChannel(1), pulse.MemorySlot(1))\n",
    "\n",
    "measure_sched = pulse.Play(meas_pulse, pulse.MeasureChannel(0)) | pulse.Play(meas_pulse, pulse.MeasureChannel(1)) | acq_sched\n",
    "\n",
    "inst_map = pulse.InstructionScheduleMap()\n",
    "inst_map.add('measure', qubits, measure_sched)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, construct the Rabi schedules."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# construct Rabi experiments\n",
    "drive_amps = np.linspace(0, 0.9, 48)\n",
    "drive_sigma = 16\n",
    "drive_duration = 128\n",
    "drive_channels = [pulse.DriveChannel(0), pulse.DriveChannel(1)]\n",
    "\n",
    "\n",
    "rabi_experiments, rabi_amps = rabi_schedules(amp_list=drive_amps, \n",
    "                                             qubits=qubits, \n",
    "                                             pulse_width=drive_duration, \n",
    "                                             pulse_sigma=drive_sigma,\n",
    "                                             drives=drive_channels,\n",
    "                                             inst_map=inst_map,\n",
    "                                             meas_map=[[0, 1]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `Schedule`s in `rabi_schedules` correspond to experiments to generate Rabi oscillations on both qubits in parallel. Each experiment consists of a Gaussian pulse on the qubits of a given magnitude, followed by measurement.\n",
    "\n",
    "For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x864 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rabi_experiments[10].draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 Simulate the Rabi experiments\n",
    "\n",
    "To simulate the Rabi experiments, assemble the `Schedule` list into a qobj. When assembling, pass the `PulseSimulator` as the backend.\n",
    "\n",
    "Here, we want to use local oscillators with frequencies automatically computed from Duffing model Hamiltonian."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# instantiate the pulse simulator\n",
    "backend_sim = PulseSimulator()\n",
    "\n",
    "# compute frequencies from the Hamiltonian\n",
    "qubit_lo_freq = two_qubit_model.hamiltonian.get_qubit_lo_from_drift()\n",
    "\n",
    "rabi_qobj = assemble(rabi_experiments, \n",
    "                     backend=backend_sim, \n",
    "                     qubit_lo_freq=qubit_lo_freq,\n",
    "                     meas_level=1, \n",
    "                     meas_return='avg',\n",
    "                     shots=512)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the simulation using the simulator backend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# run the simulation\n",
    "rabi_result = backend_sim.run(rabi_qobj, two_qubit_model).result()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3 Fit and plot the data\n",
    "\n",
    "Next, we use `RabiFitter` in Ignis to fit the data, extract the $\\pi$-pulse amplitude, and then plot the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pi Amp: 0.310790\n",
      "Pi Amp: 0.313279\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rabifit = RabiFitter(rabi_result, rabi_amps, qubits, fit_p0 = [0.5,0.5,0.6,1.5])\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "q_offset = 0\n",
    "for qubit in qubits:\n",
    "    ax = plt.subplot(2, 2, qubit + 1)\n",
    "    rabifit.plot(qubit, ax=ax)\n",
    "    print('Pi Amp: %f'%rabifit.pi_amplitude(qubit))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotted is the averaged IQ data for observing each qubit. Observe that here, each qubit oscillates between the 0 and 1 state. The amplitude at which a given qubit reaches the peak of the oscillation is the desired $\\pi$-pulse amplitude."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Oscillations from cross-resonance drive <a name='cr'></a>\n",
    "\n",
    "Next, we simulate the effects of a cross-resonance drive on qubit $1$ with target qubit $0$, observing that the trajectory and oscillations of qubit $0$ *depends* on the state of qubit $1$.\n",
    "\n",
    "**Note:** This section depends on the $\\pi$-pulse calibrations of Section 2."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1 Cross-resonance `ControlChannel` indices\n",
    "\n",
    "Driving qubit $1$ at the frequency of qubit $0$ requires use of a pulse `ControlChannel`. The model generating function `duffing_system_model`, automatically sets up `ControlChannels` for performing cross-resonance drives between pairs of coupled qubits. The index of the `ControlChannel` for performing a particular cross-resonance drive is retrievable using the class method `control_channel_index` on the returned `PulseSystemModel`. For example, to get the `ControlChannel` index corresponding to a CR drive on qubit 1 with target 0, call the function `control_channel_index` with the tuple `(1,0)`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "two_qubit_model.control_channel_index((1,0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hence, to perform a cross-resonance drive on qubit $1$ with target qubit $0$, use `ControlChannel(1)`. This will be made use of when constructing `Schedule` objects in this section."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2 Functions to generate the experiment list, and analyze the output\n",
    "\n",
    "First, we define a function `cr_drive_experiments`, which, given the drive and target indices, and the option to either start with the drive qubit in the ground or excited state, returns a list of experiments for observing the oscillations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# store the pi amplitudes from Section 2 in a list\n",
    "pi_amps = [rabifit.pi_amplitude(0), rabifit.pi_amplitude(1)]\n",
    "\n",
    "def cr_drive_experiments(drive_idx, \n",
    "                         target_idx, \n",
    "                         flip_drive_qubit = False,\n",
    "                         cr_drive_amps=np.linspace(0, 0.9, 16),\n",
    "                         cr_drive_samples=800,\n",
    "                         cr_drive_sigma=4,\n",
    "                         pi_drive_samples=128,\n",
    "                         pi_drive_sigma=16):\n",
    "    \"\"\"Generate schedules corresponding to CR drive experiments.\n",
    "\n",
    "    Args:\n",
    "        drive_idx (int): label of driven qubit\n",
    "        target_idx (int): label of target qubit\n",
    "        flip_drive_qubit (bool): whether or not to start the driven qubit in the ground or excited state\n",
    "        cr_drive_amps (array): list of drive amplitudes to use\n",
    "        cr_drive_samples (int): number samples for each CR drive signal\n",
    "        cr_drive_sigma (float): standard deviation of CR Gaussian pulse\n",
    "        pi_drive_samples (int): number samples for pi pulse on drive\n",
    "        pi_drive_sigma (float): standard deviation of Gaussian pi pulse on drive\n",
    "\n",
    "    Returns:\n",
    "        list[Schedule]: A list of Schedule objects for each experiment\n",
    "    \"\"\"\n",
    "    \n",
    "    # Construct measurement commands to be used for all schedules\n",
    "    meas_amp = 0.025\n",
    "    meas_samples = 1200\n",
    "    meas_sigma = 4\n",
    "    meas_width = 1150\n",
    "    meas_pulse = GaussianSquare(duration=meas_samples, amp=meas_amp,\n",
    "                               sigma=meas_sigma, width=meas_width)\n",
    "\n",
    "    acq_sched = pulse.Acquire(meas_samples, pulse.AcquireChannel(0), pulse.MemorySlot(0))\n",
    "    acq_sched += pulse.Acquire(meas_samples, pulse.AcquireChannel(1), pulse.MemorySlot(1))\n",
    "    \n",
    "    # create measurement schedule\n",
    "    measure_sched = (pulse.Play(meas_pulse, pulse.MeasureChannel(0)) | \n",
    "                     pulse.Play(meas_pulse, pulse.MeasureChannel(1))| \n",
    "                     acq_sched)\n",
    "    \n",
    "    # Create schedule\n",
    "    schedules = []\n",
    "    for ii, cr_drive_amp in enumerate(cr_drive_amps):\n",
    "        \n",
    "        # pulse for flipping drive qubit if desired\n",
    "        pi_pulse = Gaussian(duration=pi_drive_samples, amp=pi_amps[drive_idx], sigma=pi_drive_sigma)\n",
    "\n",
    "        # cr drive pulse\n",
    "        cr_width = cr_drive_samples - 2*cr_drive_sigma*4\n",
    "        cr_rabi_pulse = GaussianSquare(duration=cr_drive_samples, \n",
    "                                       amp=cr_drive_amp, \n",
    "                                       sigma=cr_drive_sigma,\n",
    "                                       width=cr_width)\n",
    "\n",
    "        # add commands to schedule\n",
    "        schedule = pulse.Schedule(name='cr_rabi_exp_amp_%s' % cr_drive_amp)\n",
    "\n",
    "        # flip drive qubit if desired\n",
    "        if flip_drive_qubit:\n",
    "            schedule += pulse.Play(pi_pulse, pulse.DriveChannel(drive_idx))\n",
    "        \n",
    "        # do cr drive\n",
    "        # First, get the ControlChannel index for CR drive from drive to target\n",
    "        cr_idx = two_qubit_model.control_channel_index((drive_idx, target_idx))\n",
    "        schedule += pulse.Play(cr_rabi_pulse, pulse.ControlChannel(cr_idx))  << schedule.duration\n",
    "        \n",
    "        \n",
    "        schedule += measure_sched << schedule.duration\n",
    "\n",
    "        schedules.append(schedule)\n",
    "    return schedules"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we create two functions for observing the data:\n",
    "\n",
    "- `plot_cr_pop_data` - for plotting the oscillations between the ground state and the first excited state\n",
    "- `plot_bloch_sphere` - for viewing the trajectory of the target qubit on the bloch sphere"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_cr_pop_data(drive_idx, \n",
    "                     target_idx, \n",
    "                     sim_result, \n",
    "                     cr_drive_amps=np.linspace(0, 0.9, 16)):\n",
    "    \"\"\"Plot the population of each qubit.\n",
    "\n",
    "    Args:\n",
    "        drive_idx (int): label of driven qubit\n",
    "        target_idx (int): label of target qubit\n",
    "        sim_result (Result): results of simulation\n",
    "        cr_drive_amps (array): list of drive amplitudes to use for axis labels\n",
    "    \"\"\"\n",
    "    \n",
    "    amp_data_Q0 = []\n",
    "    amp_data_Q1 = []\n",
    "\n",
    "    for exp_idx in range(len(cr_drive_amps)):\n",
    "        exp_mem = sim_result.get_memory(exp_idx)\n",
    "        amp_data_Q0.append(np.abs(exp_mem[0]))\n",
    "        amp_data_Q1.append(np.abs(exp_mem[1]))\n",
    "\n",
    "    plt.plot(cr_drive_amps, amp_data_Q0, label='Q0')\n",
    "    plt.plot(cr_drive_amps, amp_data_Q1, label='Q1')\n",
    "    plt.legend()\n",
    "    plt.xlabel('Pulse amplitude, a.u.', fontsize=20)\n",
    "    plt.ylabel('Signal, a.u.', fontsize=20)\n",
    "    plt.title('CR (Target Q{0}, driving on Q{1})'.format(target_idx, drive_idx), fontsize=20)\n",
    "    plt.grid(True)\n",
    "\n",
    "def bloch_vectors(drive_idx, drive_energy_level, sim_result):\n",
    "    \"\"\"Plot the population of each qubit.\n",
    "\n",
    "    Args:\n",
    "        drive_idx (int): label of driven qubit\n",
    "        drive_energy_level (int): energy level of drive qubit at start of CR drive\n",
    "        sim_result (Result): results of simulation\n",
    "    \n",
    "    Returns:\n",
    "        list: list of Bloch vectors corresponding to the final state of the target qubit\n",
    "              for each experiment\n",
    "    \"\"\"\n",
    "    \n",
    "    # get the dimension used for simulation\n",
    "    dim = int(np.sqrt(len(sim_result.get_statevector(0))))\n",
    "    \n",
    "    \n",
    "    # get the relevant dressed state indices\n",
    "    idx0 = 0\n",
    "    idx1 = 0\n",
    "    if drive_idx == 0:\n",
    "        if drive_energy_level == 0:\n",
    "            idx0, idx1 = 0, dim\n",
    "        elif drive_energy_level == 1:\n",
    "            idx0, idx1 = 1, dim + 1\n",
    "    if drive_idx == 1:\n",
    "        if drive_energy_level == 0:\n",
    "            idx0, idx1 = 0, 1\n",
    "        elif drive_energy_level == 1:\n",
    "            idx0, idx1 = dim, dim + 1\n",
    "\n",
    "    # construct Pauli operators for correct dressed manifold\n",
    "    state0 = np.array([two_qubit_model.hamiltonian._estates[idx0]])\n",
    "    state1 = np.array([two_qubit_model.hamiltonian._estates[idx1]])\n",
    "    \n",
    "    outer01 = np.transpose(state0)@state1\n",
    "    outer10 = np.transpose(state1)@state0\n",
    "    outer00 = np.transpose(state0)@state0\n",
    "    outer11 = np.transpose(state1)@state1\n",
    "    \n",
    "    X = outer01 + outer10\n",
    "    Y = -1j*outer01 + 1j*outer10\n",
    "    Z = outer00 - outer11\n",
    "    \n",
    "    # function for computing a single bloch vector\n",
    "    bloch_vec = lambda vec: np.real(np.array([np.conj(vec)@X@vec, np.conj(vec)@Y@vec, np.conj(vec)@Z@vec]))\n",
    "    \n",
    "    return [bloch_vec(sim_result.get_statevector(idx)) for idx in range(len(sim_result.results))]\n",
    "\n",
    "def plot_bloch_sphere(bloch_vectors):\n",
    "    \"\"\"Given a list of Bloch vectors, plot them on the Bloch sphere\n",
    "\n",
    "    Args:\n",
    "        bloch_vectors (list): list of bloch vectors\n",
    "    \"\"\"\n",
    "    sphere = Bloch()\n",
    "    sphere.add_points(np.transpose(bloch_vectors))\n",
    "    sphere.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3 Drive qubit 1 to observe CR oscillations on qubit 0\n",
    "\n",
    "#### Qubit 1 in the ground state\n",
    "\n",
    "First, we drive with both qubit 0 and qubit 1 in the ground state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# construct experiments\n",
    "drive_idx = 1\n",
    "target_idx = 0\n",
    "flip_drive = False\n",
    "experiments = cr_drive_experiments(drive_idx, target_idx, flip_drive)\n",
    "\n",
    "# compute frequencies from the Hamiltonian\n",
    "qubit_lo_freq = two_qubit_model.hamiltonian.get_qubit_lo_from_drift()\n",
    "\n",
    "# assemble the qobj\n",
    "cr_rabi_qobj = assemble(experiments,\n",
    "                        backend=backend_sim,\n",
    "                        qubit_lo_freq=qubit_lo_freq,\n",
    "                        meas_level=1, \n",
    "                        meas_return='avg',\n",
    "                        shots=512)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the simulation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_result = backend_sim.run(cr_rabi_qobj, two_qubit_model).result()\n",
    "\n",
    "plot_cr_pop_data(drive_idx, target_idx, sim_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observe that qubit 1 remains in the ground state, while excitations are driven in qubit 0.\n",
    "\n",
    "We may also observe the trajectory of qubit 0 on the Bloch sphere:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bloch_vecs = bloch_vectors(drive_idx, int(flip_drive), sim_result)\n",
    "plot_bloch_sphere(bloch_vecs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Qubit 1 in the first excited state\n",
    "\n",
    "Next, we again perform a CR drive qubit 1 with qubit 0 as the target, but now we start each experiment by flipping qubit 1 into the first excited state. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# construct experiments, now with flip_drive == True\n",
    "drive_idx = 1\n",
    "target_idx = 0\n",
    "flip_drive = True\n",
    "experiments = cr_drive_experiments(drive_idx, target_idx, flip_drive)\n",
    "\n",
    "# compute frequencies from the Hamiltonian\n",
    "qubit_lo_freq = two_qubit_model.hamiltonian.get_qubit_lo_from_drift()\n",
    "\n",
    "# assemble the qobj\n",
    "cr_rabi_qobj = assemble(experiments,\n",
    "                        backend=backend_sim,\n",
    "                        qubit_lo_freq=qubit_lo_freq,\n",
    "                        meas_level=1, \n",
    "                        meas_return='avg',\n",
    "                        shots=512)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_result = backend_sim.run(cr_rabi_qobj, two_qubit_model).result()\n",
    "\n",
    "plot_cr_pop_data(drive_idx, target_idx, sim_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observe that now qubit 1 is in the excited state, while oscillations are again being driven on qubit 0, now at a different rate as before.\n",
    "\n",
    "Again, observe the trajectory of qubit 0 on the Bloch sphere:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bloch_vecs = bloch_vectors(drive_idx, int(flip_drive), sim_result)\n",
    "plot_bloch_sphere(bloch_vecs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we see that qubit 0 takes a *different* trajectory on the Bloch sphere when qubit 1 is in the excited state. This is what enables controlled operations between two qubits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td>Qiskit</td><td>0.19.6</td></tr><tr><td>Terra</td><td>0.14.2</td></tr><tr><td>Aer</td><td>0.5.2</td></tr><tr><td>Ignis</td><td>0.3.3</td></tr><tr><td>Aqua</td><td>0.7.3</td></tr><tr><td>IBM Q Provider</td><td>0.7.2</td></tr><tr><th>System information</th></tr><tr><td>Python</td><td>3.8.5 (default, Jul 27 2020, 08:42:51) \n",
       "[GCC 10.1.0]</td></tr><tr><td>OS</td><td>Linux</td></tr><tr><td>CPUs</td><td>32</td></tr><tr><td>Memory (Gb)</td><td>125.72603988647461</td></tr><tr><td colspan='2'>Sun Aug 09 12:28:03 2020 EDT</td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style='width: 100%; background-color:#d5d9e0;padding-left: 10px; padding-bottom: 10px; padding-right: 10px; padding-top: 5px'><h3>This code is a part of Qiskit</h3><p>&copy; Copyright IBM 2017, 2020.</p><p>This code is licensed under the Apache License, Version 2.0. You may<br>obtain a copy of this license in the LICENSE.txt file in the root directory<br> of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.<p>Any modifications or derivative works of this code must retain this<br>copyright notice, and modified files need to carry a notice indicating<br>that they have been altered from the originals.</p></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import qiskit.tools.jupyter\n",
    "%qiskit_version_table\n",
    "%qiskit_copyright"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
